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Combining shape analysis and texture pattern for palmprint identification

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Abstract

We propose an efficient method for principal line extraction from the palmprint and geometric framework for analyzing their shapes. This representation, along with the elastic Riemannian metric, seems natural for measuring principal line deformations and is robust to challenges such as orientation variation and re-parameterization due to pose variation and missing part, respectively. The palmprint texture is investigated using the fractal analysis; thus the resulting features are fused with the principal line features. This framework is shown to be promising from both – empirical and theoretical – perspectives. In terms of empirical evaluation, our results match or improve the state-of-the-art methods on three prominent palmprint datasets: PolyU, CASIA, and IIT-Delhi, each posing a different type of challenge. From a theoretical perspective, this framework allows fusing texture analysis and shape analysis.

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  1. A Java plug-in is available at http://bigwww.epfl.ch.

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Acknowledgments

The authors would like to thank Pr. Mohamed Daoudi from the CRIStAL laboratory, France for his assistance and cooperation about this work.

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Authors and Affiliations

  1. Faculty of Economics and Management of Sfax (FSEGS), University of Sfax, Sfax, Tunisia

    Raouia Mokni

  2. The Institut Mines-Télécom/Télécom Lille, CRIStAL (UMR CNRS 9189), Villeneuve-d’Ascq, France

    Hassen Drira

  3. Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia

    Monji Kherallah

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  1. Raouia Mokni
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  2. Hassen Drira
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  3. Monji Kherallah
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Correspondence to Raouia Mokni.

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Mokni, R., Drira, H. & Kherallah, M. Combining shape analysis and texture pattern for palmprint identification. Multimed Tools Appl 76, 23981–24008 (2017). https://doi.org/10.1007/s11042-016-4088-5

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  • DOI: https://doi.org/10.1007/s11042-016-4088-5

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